#the first set of testing problems for the IPC 2014 competitors # this is intended to be an easier problemset that: # (1) thins out the final list of competitors I need to # run to determine a winner of each category # (2) provides the baseline for who will be considered # for the best learner prize #method for generation (prior to observing results from testing on training): # (1) take the testing subset from "testingFromTraining.txt" # (2) for each problem, randomly select new parameters within # the range of the problems in that set. # (3) Generate random numbers with Python 2.7.3 (default, Feb 27 2014, 20:00:17) # random.randint() function, which generates a number, N, in the # range R1, R2: R1 <= N <= R2. At the start of each problem, I set # the seed to "2014" for the first problem and seed to 2014N, # where N is 2 thru 6 for other problems. I then draw each number # from randint( R1, R2 ), observing the random sequence. # elevators - p[floors]_[passengers].pddl # p24_45_1.pddl # p32_45_1.pddl # p40_45_1.pddl # p48_45_1.pddl #create 5 problems #seed 2014 #randomly select 24,32, or 40 floors; randint(1,3): 1, 2, 3, 3, 2 #randomly select between 40 and 60 passengers; randint(40,60): 54, 40, 48, 42, 54 p24_54_1.pddl p32_40_1.pddl p40_48_1.pddl p40_42_1.pddl p32_54_1.pddl #floortile p[rows]-[cols]-[robots].pddl # p4-4-2.pddl # p5-4-2.pddl # p4-4-3.pddl # p5-5-3.pddl #create 5 problems #seed 20142 #randomly select rows between 4-6; randint(4,6): 4 5 4 6 4 #randomly select cols between between 3-6; randint(3,6): 3 4 3 4 5 #randomly select robots from 2 or 3; randint(2,3): 2 2 2 3 3 #correct second instance of 4 3 2 to 4 3 3; cannot generate probs with same name p4-3-2.pddl p5-4-2.pddl p4-3-3.pddl p6-4-3.pddl p4-5-3.pddl #nomystery p-[ratio]-[packages&locations].pddl # p-c15-08.pddl # p-c13-08.pddl # p-c11-08.pddl # p-c10-08.pddl #create 5 problems #seed 20143 #randomly select packages between 8-16; randint(8,16): 9, 10, 12, 11, 15 #randomly select locations between (-2,2); randint(-2,2): -2, -2, -2, 0, -1 #randomly select c from {1.5, 1.3, 1.1}; randint( 1,3): 3, 1, 1, 1, 1 p-c11-09-07.pddl p-c15-10-08.pddl p-c15-12-10.pddl p-c15-11-11.pddl p-c15-15-14.pddl #parking p[curbs]-[cars].pddl # p28-15.pddl # p38-20.pddl # p48-25.pddl # p58-30.pddl #create 5 problems #seed 20144 #randomly select cars between 15-30; randint(15,30): 23, 24, 28, 23, 19, 19, 30 p44-23.pddl p46-24.pddl p34-28.pddl p36-19.pddl p58-30.pddl #spanner prob-[spanners]-[nuts]-[locatins].pddl # prob-130-130-80-1396209574.pddl # prob-140-140-90-1396209574.pddl # prob-150-150-100-1396209574.pddl # prob-160-160-110-1396209574.pddl #create 5 problems #seed 20145 #randomly select num_spanners 130-160 randint(130,160): 143, 159, 150, 132, 130 #randomly select delta for num_nuts -4,4 randint(-4,4): 2, -4, 0, 3, 3 #randomly select delta for num_locs 46-54 randint(46,54): 50, 53, 47, 47, 49 prob-143-145-93-1403129508.pddl prob-159-155-106-1403129508.pddl prob-150-150-103-1403129508.pddl prob-132-135-85-1403129508.pddl prob-130-3-49-1403129508.pddl #transport p-[cities]-[locations]-[packages].pddl # p-2-50-30.pddl # p-2-60-25.pddl # p-3-50-25.pddl # p-3-60-20.pddl #generate 5 problems #seed 20146 #randomly select cities 2 or 3 randint(2,3): 3, 2, 3, 3, 3 #randomly select locations 50-60 randint(50,60): 58, 55, 55, 56, 60 #randomly select packages 20-35 randint(20,35): 27, 23, 31, 35, 27 p-3-58-27.pddl p-2-55-23.pddl p-3-55-31.pddl p-3-56-35.pddl p-3-60-27.pddl